A metabolism-associated gene signature with prognostic value in colorectal cancer*

Abstract

Abstract Objective In this study, our goal was to explore the role of metabolism-associated genes in colorectal cancer (CRC) and construct a prognostic model for patients with CRC. Methods Differential expression analysis was conducted using RNA-sequencing data from The Cancer Genome Atlas (TCGA) dataset. Enrichment analyses were performed to determine the function of dysregulated metabolism-associated genes. The protein-protein interaction (PPI) network, Kaplan-Meier curves, and stepwise Cox regression analyses identified key metabolism-associated genes. A prognostic model was constructed using LASSO Cox regression analysis and visualized as a nomogram. Survival analyses were conducted in the TCGA and Expression Omnibus (GEO) cohorts to demonstrate the predictive ability of the model. Results A total of 332 differentially expressed metabolism-associated genes in CRC were screened from the TCGA cohort. Differentially expressed metabolism-associated genes mainly participate in the metabolism of nucleoside phosphate, ribose phosphate, lipids, and fatty acids. A PPI network was constructed out of 328 key genes. A prognostic model was established based on five prognostic genes (ALAD, CHDH, ISYNA1, NAT1, and P4HA1) and was demonstrated to predict survival in the TCGA and GEO cohorts accurately. Conclusion The metabolism-associated prognostic model can predict the survival of patients with CRC. Our work supplements previous work focusing on determining prognostic factors of CRC and lays a foundation for further mechanistic exploration.